DocumentCode :
2715386
Title :
A Novel Multi-target Detecting and Tracing Method for Robot Vision System
Author :
Benjie, Wei ; Peng, Li
Author_Institution :
Center for Space Sci. & Appl. Res., Electron. Lab., Beijing, China
fYear :
2012
fDate :
11-13 Aug. 2012
Firstpage :
182
Lastpage :
186
Abstract :
In this paper we study on multi-target detecting and tracing system for intelligent robot and give a good method to detect and track the targets such as pedestrians, which needs to extract the moving targets from the background in image sequence, and track them by probability statistics and controlling theory. In the first stage, we segment the foreground and background regions through GMM (Gaussian Mixture Model) [1] algorithm. Based on the results of the first stage, we build the tracing system with Kalman filter and Mean-Shift in order to capture the moving targets. At last, the experimental results show that our method is correct and robust, it lays a solid foundation for further study on target recognition.
Keywords :
Gaussian processes; Kalman filters; image segmentation; image sequences; intelligent robots; object detection; object tracking; probability; robot vision; GMM algorithm; Gaussian mixture mode algorithm; Kalman filter; background regions; controlling theory; foreground regions; image segmentation; image sequence; intelligent robot; mean-shift algorithm; moving target extraction; novel multitarget detecting method; novel multitarget tracing method; probability statistics; robot vision system; target recognition; Computational modeling; Gaussian distribution; Kalman filters; Kernel; Prediction algorithms; Target tracking; Vectors; GMM; Kalman filter; Mean-Shift; detecting; multi-target; tracing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
Type :
conf
DOI :
10.1109/CSSS.2012.53
Filename :
6394292
Link To Document :
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